o Major Research Products:
● GA-ANN Classifier: Development of Signal-Noise Classifier combining Genetic Algorithm and Artificial Neural Networks
○ Optimization of Neural Networks via Genetic Algorithm - Higher Performing Classifier by finding optimized networks through searching global optimum
● Enhancing Signal Detection Rate of Gravitational-wave by Machine Learning
○ 10% Enhancement of signal detection sensitivity comparing conventional method
○ Random Forest, Artificial Neural Networks applied
● Development of Anomaly Detection & Extraction Algorithm based on Hilbert-Huang Transform (EtaGen)
○ Signal Anomaly Detection from Gravitational-wave Observation Data
○ Anomaly Detection in the EEG data and Finding Epilepsy Symptom - High Frequency Oscillation Search associated with Epilepy
○ Sea Level Data Analysis using Time-Series Data Analysis
- Correlation analysis between Sea Levels and Environment around Korea using CEEMDAN(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) based on Hilbert-Huang Transformation
● Abnormal Channel Monitor measured by Correlation Index (CAGMon)
○ Association between two parameter sets of data by using Pearson R, MIC, Kendall’s tau
○ Targeting the reduction of noises vis correlation analysis between noise sources and signals
● Development of Application S/W for dicriminating Climate-sensitive Biological Indicator by using Image Processing
● Hunman Brain & Traffic Network Study using Complex Networks
○ Human brain network analysis & personality: developing S/W for extracting brain connectivity from fMRI, EEG data & personality analysis for network analysis
○ Main traffic network analysis using Betweenness centrality
● Advanced data analysis computing tools using parallel & hybrid computing (VHDL, Verilog, OpenCL, MPI etc)
○ Development of RNGs, FFT modules using FPGA
○ FPGA-based programming and Burn-in test board development
○ Portable data analysis platform via high performance computation module
○ Heterogeneous computing platform and application to deep learning
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Website : http://www.nims.re.kr